get_video_transcript

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Although annotations already mark the tool as read-only, idempotent, and non-destructive, the description adds significant behavioral detail: 'Nothing is written to disk - the caption track is read straight into memory,' preference for manual over auto-generated captions, and language fallback behavior. It also discloses error conditions (ValueError, RuntimeError), which goes well beyond the annotation hints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with distinct sections for purpose, behavior, Args, Returns, and Errors. The main action is front-loaded in the first sentence, and every section provides necessary information. While it is relatively long, the length is justified by the lack of an output schema and the need to document four parameters and a complex return object.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is comprehensive: it details the full return object with field explanations, lists specific error types and when they occur, and gives practical usage tips such as setting max_chars when scanning many videos. This provides an agent with sufficient context to select and invoke the tool correctly, even without an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has no descriptions (0% coverage), so the description carries full responsibility. The Args section explains each parameter in detail: accepted video ID/URL formats, language fallback (e.g., 'en' matches 'en-US', first available track if missing), include_timestamps formatting, and max_chars truncation usage. This fully compensates for the schema gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description starts with 'Fetch a video's transcript as clean plain text,' clearly stating a specific verb and resource. It also explains the fallback to auto-generated captions, which helps distinguish this transcript-focused tool from sibling tools that list videos, search, or extract frames.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit comparison to sibling tools such as list_channel_videos, search_youtube, or get_video_frames, nor does it state when to use this tool instead of them. The usage context is implied by the tool's purpose, but there is no explicit 'use when' or 'use instead' guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.